Power Curve Explorer

Visualize how total sample size, effect size (Cohen's \(d\)), allocation ratio, and significance level impact statistical power (\(1 - \beta\)) for an independent two-sample Student's t-test (two-tailed, assuming equal variances).

Standardized difference between the means.

Ratio of sample sizes between group 2 and group 1.

Probability of a Type I error (false positive).

Target Power Requires Total \(N\):

- total samples
(Group 1: -, Group 2: -)

Understanding the Plot:

  • X-axis (Total Sample Size, \(N\)): The combined number of observations across both groups (\(N_1 + N_2\)).
  • Y-axis (Power, \(1-\beta\)): Probability of correctly rejecting a false null hypothesis.
  • Blue Line: The computed power curve based on current parameters.
  • Red Dashed Line: Your specified target power.